Heba Afify | Engineering | Editorial Board Member

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Dr. Heba Afify | Engineering | Editorial Board Member

Cairo | Egypt

Dr. Heba Afify research explores the molecular landscape of the BLIS subtype of triple-negative breast cancer through comprehensive bioinformatics analysis aimed at identifying immune-related hub genes with critical roles in tumor progression, immune evasion, and potential therapeutic responsiveness. Using integrated datasets and computational pipelines, the study performs differential gene expression profiling, network construction, and enrichment analyses to map immune-modulated pathways underlying the aggressive behavior of the BLIS subtype. Key immune hub genes are screened through protein–protein interaction networks, functional annotation, and pathway enrichment to uncover targets with relevance to cytokine signaling, chemokine interactions, and immune cell infiltration. The work further evaluates correlations between these hub genes and components of the tumor immune microenvironment, including associations with immunoregulatory checkpoints, inflammatory mediators, and effector immune cells. By combining multi-level computational evidence, the study highlights genes that may serve as biomarkers for diagnosis, prognosis, or targeted immunotherapy in patients with this difficult-to-treat cancer subtype. The analysis contributes to a deeper understanding of immunogenomic features driving BLIS-TNBC and offers a foundational framework for precision oncology strategies, emphasizing how immune-focused gene signatures can guide future translational research and therapeutic innovations in breast cancer management.

Featured Publications

Adel, H., Abdel Wahed, M., & Afify, H. M. (2025). Bioinformatics analysis for immune hub genes in BLIS subtype of triple-negative breast cancer. Egyptian Journal of Medical Human Genetics. https://doi.org/10.1186/s43042-025-00745-0

Afify, H. M., Mohammed, K. K., & Hassanien, A. E. (2025). Stress detection based EEG under varying cognitive tasks using convolution neural network. Neural Computing and Applications, Advance online publication. https://doi.org/10.1007/s00521-024-10737-7

Afify, H. M., Mohammed, K. K., & Hassanien, A. E. (2024). Insight into automatic image diagnosis of ear conditions based on optimized deep learning approach. Annals of Biomedical Engineering. https://doi.org/10.1007/s10439-023-03422-8

Waleed Algriree | Engineering | Editorial Board Member

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Dr. Waleed Algriree | Engineering | Editorial Board Member

Putra university malaysia | Malaysia

Dr. Waleed Algriree research contributions focus extensively on advanced communication systems, particularly the development and optimization of next-generation wireless and satellite technologies. Core work includes enhancing 5G detection performance through hybrid filtering techniques, low-complexity MIMO architectures, and multi-user spectrum sensing approaches designed to support cognitive radio environments. Significant studies investigate waveform detection using windowed cosine-Hamming filters, hybrid detection frameworks, and comparative evaluations of M-ary modulation impacts on signal identification accuracy. Additional research explores OFDM performance improvement through PAPR reduction using 2D inverse discrete Fourier transforms, as well as analytical derivations related to SLM clipping levels, complexity, and bit-loss characteristics. Contributions extend to the design of novel detection schemes employing discrete cosine transforms with QPSK modulation for cognitive radio systems, along with multi-user CR-5G network models that enhance spectral efficiency and sensing reliability across various waveform structures. Work in satellite and mobile communication further supports improved signal processing, system optimization, and robust network performance. Results published in reputable journals and conferences demonstrate strong emphasis on algorithmic efficiency, spectral utilization, advanced filter design, and practical applicability in sustainable, high-capacity communication infrastructures. These studies collectively advance the evolution of intelligent, adaptive, and efficient wireless communication technologies.

Featured Publication

Algriree, W. K. H. (Year). Advancing healthcare through piezoresistive pressure sensors: A comprehensive review of biomedical applications and performance metrics.

Mujeeb Abiola Abdulrazaq | engineering | Young Scientist Award

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Mr. Mujeeb Abiola Abdulrazaq l engineering
| Young Scientist Award

University of North Carolina at Charlotte | United States

Mr. Mujeeb Abiola’s research focuses on advancing transportation safety and efficiency through data-driven methodologies and emerging technologies. His work extensively employs large-scale traffic and crash data, including millions of federal highway administration records, to investigate the spatiotemporal dynamics of pedestrian crashes and the evolution of crash hotspots. Utilizing advanced statistical and machine learning models, he has developed predictive frameworks that outperform traditional Highway Safety Manual standards, providing robust insights into risk factors and injury severity in both human-driven and autonomous vehicle contexts. His research on connected and autonomous vehicles (CAVs) has led to the development of traffic control algorithms that significantly enhance safety, operational efficiency, and environmental sustainability in freeway work zones. Furthermore, his studies integrate GPU-accelerated data processing, simulation-based optimization, and multi-level heterogeneity modeling to evaluate vulnerable road user behavior and assess dynamic collision risks. Through simulation platforms such as VISSIM and SUMO, combined with Python-based data analysis and GIS applications, his work systematically addresses complex traffic scenarios, including merging, diverging, and weaving segments, while also accounting for seasonal variations and temporal constraints in crash determinants. His contributions include empirical analyses of autonomous vehicle incidents, methodological advancements in microsimulation accuracy, and development of actionable strategies for real-world traffic management, ultimately aiming to improve roadway safety, inform policy, and guide evidence-based planning in modern transportation systems.

Profile:Β  Google ScholarΒ 

Featured Publications

  • Abdulrazaq, M. A., & Fan, W. D. (2024). Temporal dynamics of pedestrian injury severity: A seasonally constrained random parameters approach. International Journal of Transportation Science and Technology, 9.

  • Abdulrazaq, M. A., & Fan, W. (2025). A priority based multi-level heterogeneity modelling framework for vulnerable road users. Transportmetrica A: Transport Science, 1–34. https://doi.org/10.1080/23249935.2025.2516817

  • Abdulrazaq, M. A., & Fan, W. (2025). Seasonal instability in crash determinants: A partially temporally constrained modeling analysis. SSRN 5341417. https://doi.org/10.2139/ssrn.5341417

Sheharyar Khan | Engineering | Young Scientist Award

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Dr. Sheharyar Khan l Engineering
| Young Scientist Award

Shandong University | Pakistan

Dr. Sheharyar Khan is a distinguished computer scientist and software engineer with extensive expertise in software engineering, artificial intelligence, and cybersecurity, specializing in IoMT edge-cloud frameworks and network intrusion detection systems. Currently a Postdoctoral Research Fellow at Shandong University, he leads independent and collaborative research initiatives, designing experiments, analyzing data, and publishing findings in high-impact journals. His doctoral research at Northwestern Polytechnical University focused on optimization-based hybrid offloading frameworks for IoMT in edge-cloud healthcare systems, demonstrating the integration of advanced computing techniques with practical healthcare applications. Dr. Khan has made significant contributions to explainable AI and hybrid ensemble machine learning, as seen in publications such as β€œHCIVAD: Explainable hybrid voting classifier for network intrusion detection systems” and β€œConsensus hybrid ensemble machine learning for intrusion detection with explainable AI”. With prior experience as a lecturer and IT specialist, he combines academic rigor with practical software development expertise. Dr. Khan has 104 citations across 10 documents, an h-index of 6, an i10-index of 5, is indexed under Scopus Author ID 57221647889, and holds ORCID 0000-0002-0089-0168, reflecting his impact on the field. Recognized for his analytical skills, innovation, and interdisciplinary research, he continues to advance secure, intelligent, and explainable computing systems for both academic and real-world applications.

Profile: Scopus | Google Scholar | Orcid | ResearchgateΒ 

Featured Publications

Khan, S., Liu, S., Pan, L., & Mei, G. (2025). Optimization-based hybrid offloading framework for IoMT in edge-cloud healthcare systems. Future Generation Computer Systems, 108163. https://doi.org/

Ahmed, S. K. M. T. S., Jiangbin, Z., & Khan, S. (2025). HCIVAD: Explainable hybrid voting classifier for network intrusion detection systems. Cluster Computing, 28(343). https://doi.org/

Ahmed, M. T. S., Jiangbin, Z., & Khan, S. (2024). Consensus hybrid ensemble machine learning for intrusion detection with explainable AI. Journal of Network and Computer Applications, 5*. https://doi.org/

Khan, S., Jiangbin, Z., & Ali, H. (2024). Soft computing approaches for dynamic multi-objective evaluation of computational offloading: A literature review. Cluster Computing, 27(9), 12459–12481. https://doi.org/

Manila Mallik | Engineering | Best Researcher Award

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Dr. Manila Mallik | Engineering | Best Researcher Award

Assistant Professor at VEER SURENDRA SAI UNIVERSITY OF TECHNOLOGY, BURLA, India

Dr. Manila Mallik is an accomplished academic and researcher in the field of Metallurgical and Materials Engineering. She earned her Ph.D. from the Indian Institute of Technology, Kharagpur, in 2016, with a focus on lead-free solder materials and their characterization. With a solid background in various areas including thin films, nanomaterials, electrochemistry, and industrial waste utilization, Dr. Mallik has actively contributed to both research and teaching. She has published several research papers in renowned journals, presented at numerous national and international conferences, and is an expert in materials characterization techniques like X-ray diffraction, SEM, and atomic force microscopy. Currently, she serves as an Assistant Professor at Veer Surendra Sai University of Technology, Burla, and has guided several Ph.D. and M.Tech students. Dr. Mallik is also known for her involvement in organizing seminars, workshops, and academic events, and has received multiple awards for her contributions to the field.

Professional ProfileΒ 

Education

Dr. Manila Mallik’s educational journey reflects her dedication to the field of Metallurgical and Materials Engineering. She completed her Bachelor of Technology (B.Tech) in Metallurgical Engineering from the National Institute of Technology, Rourkela, in 2009, where she developed a strong foundation in materials science. Dr. Mallik then pursued her Master’s degree (M.Tech) in Metallurgical Engineering from the Indian Institute of Technology (IIT) Kharagpur, graduating in 2011. Her exceptional academic performance led her to continue her research at IIT Kharagpur, where she completed her Ph.D. in 2016. Her doctoral research focused on lead-free solder materials, where she extensively studied their mechanical properties and characterization techniques. Throughout her academic career, Dr. Mallik has been committed to advancing her knowledge and expertise in materials science, contributing significantly to both her research field and the education of future engineers and researchers.

Professional Experience

Dr. Manila Mallik has extensive professional experience in the field of Metallurgical and Materials Engineering, with a focus on both academia and industry. She began her career as a Lecturer in the Department of Metallurgical Engineering at the National Institute of Technology (NIT), Rourkela, where she contributed to teaching and research from 2011 to 2014. Following her doctoral studies, Dr. Mallik worked as an Assistant Professor at the same institution, where she continued to teach and mentor undergraduate and postgraduate students while advancing her research on materials science. Her expertise in lead-free solder materials led her to collaborate on several research projects, including industry-sponsored work. Dr. Mallik has also held various academic roles such as research coordinator and has published numerous papers in international journals and conferences. Her career is distinguished by her commitment to bridging the gap between academic research and practical applications in materials engineering.

Research Interest

Dr. Manila Mallik’s research interests lie at the intersection of materials science, metallurgy, and engineering, with a particular focus on the development and evaluation of lead-free solder materials. Her work investigates the mechanical, thermal, and microstructural properties of these materials, exploring alternatives to traditional lead-based solders for use in electronics and other industrial applications. Dr. Mallik is also interested in the design and optimization of advanced materials for electronic and energy-efficient devices, emphasizing their durability and performance under various operating conditions. Her research extends to areas such as corrosion behavior, fatigue analysis, and material degradation, particularly in the context of environmentally sustainable materials. Additionally, Dr. Mallik explores the impact of processing techniques on the properties of materials, utilizing computational modeling and experimental approaches to enhance material performance. Her research aims to contribute to the development of safer, more reliable materials for a wide range of technological and industrial applications.

Award and Honor

Dr. Manila Mallik has received numerous awards and honors in recognition of her significant contributions to the fields of materials science and metallurgy. Her research on lead-free solder materials and sustainable engineering practices has earned her accolades at both national and international levels. Dr. Mallik was awarded the prestigious Young Scientist Award for her innovative work on materials development in electronic devices. Additionally, she has been recognized with the Excellence in Research Award for her pioneering research in the field of corrosion behavior and materials degradation. Her work has been widely published in high-impact journals, and she has received the Best Paper Award for several of her research articles. Dr. Mallik’s outstanding academic achievements have also earned her scholarships and grants from prominent research organizations. These awards reflect her dedication to advancing sustainable engineering solutions and her ongoing commitment to driving innovations that benefit society and industry alike.

Conclusion

Dr. Manila Mallik exhibits a solid academic background, diverse research interests, and strong hands-on technical expertise, making her a strong candidate for the Best Researcher Award. Her contributions to materials science, particularly in lead-free solder materials and nanocomposites, demonstrate her commitment to addressing global challenges through scientific innovation. With continued growth in industry partnerships, interdisciplinary research, and public outreach, Dr. Mallik has the potential to further elevate her already impressive career, contributing even more significantly to both academia and industry.

Publications Top Noted

  • Title: Substrate effect on electrodeposited copper morphology and crystal shapes
    Authors: S Banthia, S Sengupta, M Mallik, S Das, K Das
    Year: 2018
    Citation: 39
  • Title: Effect of current density on the nucleation and growth of crystal facets during pulse electrodeposition of Sn–Cu lead-free solder
    Authors: M Mallik, A Mitra, S Sengupta, K Das, RN Ghosh, S Das
    Year: 2014
    Citation: 35
  • Title: Investigation on lithium conversion behavior and degradation mechanisms in Tin based ternary component alloy anodes for lithium ion batteries
    Authors: S Sengupta, A Mitra, PP Dahiya, A Kumar, M Mallik, K Das, SB Majumder, …
    Year: 2017
    Citation: 19
  • Title: Effect of anodic passivation at high applied potential difference on the crystal shape and morphology of copper electrodeposits: thermodynamics and kinetics of …
    Authors: A Mitra, M Mallik, S Sengupta, S Banthia, K Das, S Das
    Year: 2017
    Citation: 15
  • Title: Corrosion inhibition behavior of dual phase steel in 3.5 wt% NaCl solution by Carica papaya peel extracts
    Authors: S Sahoo, S Nayak, D Sahoo, M Mallik
    Year: 2019
    Citation: 8
  • Title: Potential utilization of LD slag and waste glass in composite production
    Authors: M Mallik, S Hembram, D Swain, G Behera
    Year: 2020
    Citation: 7
  • Title: Pseudo lamellae of Cu6Sn5 on the crystal facet of Sn in electrodeposited eutectic Sn-Cu lead-free solder
    Authors: M Mallik, K Das, RN Ghosh, S Das
    Year: 2024
    Citation: 3
  • Title: Effect of temperature and pressure on diffusivity of nitinol pellet bonded with steel plate
    Authors: I Tripathy, SP Rout, M Mallik
    Year: 2020
    Citation: 3
  • Title: Production of copper powder by electrodeposition with different equilibrium crystal shape
    Authors: B Nanda, M Mallik
    Year: 2020
    Citation: 2
  • Title: Fatigue Crack Initiation and Growth Behavior of 7475 Aluminium Alloy in Air and Aggressive Environment
    Authors: RPK Verma B.B., Mallik Manila, Atkinson John D
    Year: 2012
    Citation: 2
  • Title: Effect of microstructure on the indentation creep behaviour of 2.25 Cr-1Mo and its comparison with modified 9Cr-1Mo ferritic steel
    Authors: M Mallik
    Year: 2011
    Citation: 2
  • Title: Effect of Cetyl Trimethyl ammonium bromide (CTAB) amount on the Nanoindentation creep behaviour of Sn-cu-Y2O3 nanocomposite Lead-free solder
    Authors: M Mallik, K Das, RN Ghosh, S Das
    Year: 2024
    Citation: 1
  • Title: 3D Printing of Smart Materials: A Path toward Evolution of 4D Printing
    Authors: M Mallik
    Year: 2022
    Citation: 1
  • Title: Electrochemical behavior of 250-grade maraging steel by using Cascabela Thevetia as an organic inhibitor
    Authors: S Sahoo, AA Sahu, A Pradhan, SR Barik, A Mohanty, M Mallik
    Year: 2024
    Citation: 1
  • Title: Synthesis of hydroxyapatite nanocomposite coating by electrodeposition route: a state of the art review
    Authors: BK Karali, S Das, G Behera, M Mallik
    Year: 2024
    Citation: 1
  • Title: Flexible PMN-PT/rGO/PVDF-TrFE based composites for triboelectric and piezoelectric energy harvesting
    Authors: S Das, M Mallik, K Parida, N Bej, J Baral
    Year: 2024
    Citation: 1
  • Title: Microstructural characteristics of flexible ceramics
    Authors: S Das, K Parida, N Bej, M Mallik
    Year: 2023
    Citation: 1

Adrian Pisla | Engineering | Best Researcher Award

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Adrian Pisla | Engineering | Best Researcher Award

Prof Adrian Pisla, Technical University in Cluj-Napoca, Romania

Prof. Adrian Pisla is a renowned University Professor at the Technical University of Cluj-Napoca, Romania, specializing in engineering and management. He holds extensive academic experience, having served as Assistant Professor, Associate Professor, and University Professor. Additionally, he supervises PhD students and leads the Dynamic Systems Simulation Laboratory. He has received numerous accolades, including the “Traian Vuia” prize and gold medals for his innovations in robotics. His work includes research in parallel robotics, rehabilitation systems, and sustainability. Prof. Pisla has authored impactful publications and contributed to e-learning systems, with expertise in mechanical design and robotics. πŸ…πŸ€–πŸŽ“

Publication Profile

google scholar

Education

Prof. Adrian Pisla has an extensive background in higher education, training, and product development. His academic achievements include the completion of various courses and training programs across Europe and the USA, such as EinfΓΌhrung in die Hochschuldidaktik at BabeΘ™-Bolyai University and specialized courses in product development using Siemens PLM. Prof. Pisla has participated in international programs on online education, environmental management, and automation systems, with notable roles in Clusters Management Mentoring. His Ph.D. in Computer-Aided Manufacturing, awarded by the Technical University in Cluj-Napoca, focused on thermal spraying technology. He has contributed significantly to interdisciplinary education and technology development. πŸŽ“πŸŒπŸ’»πŸ› 

Experience

Prof. Adrian Pisla’s career began in 1987 as an Engineer in Probation at IMMR Pascani, Romania. He transitioned to Design Engineer at IMMR “16 Februarie” in Cluj-Napoca in 1990, followed by a role as an Analyst-Programmer in the same company. In 1991, he joined the Technical University of Cluj-Napoca as a Teaching Assistant and later advanced to Assistant Professor in 1995. From 1998 to 2002, he served as an Associate Professor, and in 2002, he became a University Professor at the same institution. His academic journey highlights his dedication to education and engineering. πŸ“šπŸ’‘πŸ‘¨β€πŸ«

International Recognition

Prof. Pisla’s remarkable accomplishments have earned him international recognition. In 2023, he received the prestigious lifetime achievement award from the Romanian Academy, honoring his outstanding contributions to his field. His innovative work has also been acknowledged through multiple medals at renowned international innovation exhibitions. These accolades highlight his dedication to advancing knowledge and fostering groundbreaking research. With his influential impact on academia and innovation, Prof. Pisla continues to inspire the global scientific community. πŸ…πŸŒπŸ”¬πŸ†πŸŽ“

Awards and Distinctions

He has received numerous prestigious accolades, including multiple gold and bronze medals at various international research and innovation events. These awards serve as a testament to the exceptional quality and impact of his work, highlighting his dedication and expertise in his field. His achievements not only reflect his intellectual abilities but also his commitment to advancing knowledge and innovation on a global scale. These recognitions are a clear affirmation of his ability to contribute groundbreaking solutions that make a significant difference. πŸ₯‡πŸ…πŸŒπŸ’‘

Research Focus

Prof. Adrian Pisla’s research focuses on the design, development, and application of robotic systems, particularly in the fields of rehabilitation, surgery, and automation. His work spans parallel robotics for lower and upper limb rehabilitation, kinematics, and virtual reality simulators for medical applications. He also explores the risk-based assessment of robotic systems used in post-stroke rehabilitation and minimal invasive surgery. Additionally, he is involved in sustainable automation practices and digital agriculture. Prof. Pisla’s expertise includes engineering, robotics, and life cycle management of robotic technologies, contributing significantly to healthcare robotics and automation advancements. πŸ€–πŸ¦ΎπŸ’‘πŸ’‰πŸŒ±

Publication Top Notes

Systematic design of a parallel robotic system for lower limb rehabilitation

Agile, waterfall and iterative approach in information technology projects

Risk-based assessment engineering of a parallel robot used in post-stroke upper limb rehabilitation

Kinematics and design of a 5-DOF parallel robot used in minimally invasive surgery

Development of a virtual reality simulator for an intelligent robotic system used in ankle rehabilitation

Kinematical analysis and design of a new surgical parallel robot

TABASUM GULEDGUDD | Engineering | Best Researcher Award

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TABASUM GULEDGUDD | Engineering | Best Researcher Award

Ms TABASUM GULEDGUDD, SECAB INSTITUTE OF ENGINEERING AND TECHNOLOGY, India

Tabasum Guledgudd is an Assistant Professor and Head of the Department of Electronics and Communication Engineering at SECAB Institute of Engineering and Technology, Vijayapur, with over 12 years of experience in teaching and academic administration. She has contributed to NBA accreditation, organizing workshops, faculty recruitment, and guiding students on government-funded projects. Her research interests include IoT-based health monitoring systems, VLSI, and Embedded Systems. She has published articles in prominent journals, such as the African Journal of Biomedical Research and the African Journal of Science, Technology, Innovation, and Development. She is also actively involved in workshops and FDPs. πŸ“šπŸ’‘πŸ–₯οΈπŸŽ“

Publication Profile

Orcid

Academic ProfileΒ 

Tabasum holds a Bachelor’s degree in Electronics and Communication Engineering (2007) from Visvesvaraya Technology University, Belagavi, and an M.Tech. in VLSI & Embedded Systems (2013) from Jawaharlal Nehru Technological University, Hyderabad. Currently, she is pursuing her Ph.D. (Part-time) in Artificial Intelligence and Machine Learning (AIML) for decision-making in IoT-based health monitoring systems. She successfully completed her comprehensive viva in 2018. With a strong academic background and a focus on advanced technologies, Tabasum is dedicated to exploring innovative solutions in the intersection of AI, IoT, and healthcare. πŸ’»πŸ€–πŸ“‘πŸ“ŠπŸŽ“

Employment Record

Ms. Tabasum Guledgudd is currently serving as the Assistant Professor and Head of the Department of Electronics and Communication Engineering at SECAB Institute of Engineering and Technology, Vijayapur, since July 27, 2013. With extensive experience in academia, she has previously worked as an Assistant Professor at Sri Indu College of Engineering & Technology, Hyderabad, both from January to May 2012 and from January to December 2010. Her dedication to teaching and leadership in the field of Electronics and Communication Engineering continues to inspire students and contribute to the institution’s growth. πŸ“šπŸ‘©β€πŸ«πŸ“‘

Research Experience

Ms. Tabasum Gulegdudd has made significant contributions to academic research, with notable publications in reputable journals. In 2024, she published a comparative study on machine learning algorithms for leukemia diagnosis in the African Journal of Biomedical Research, showcasing her expertise in medical technology. Additionally, she authored a comprehensive review of integrated technologies in the Internet of Health Things (IoHT) applications, featured in the African Journal of Science, Technology, Innovation, and Development. These works highlight her dedication to advancing research and her commitment to improving healthcare through innovative technological applications. πŸ“šπŸ’»πŸ©ΊπŸ“ˆ

Previous EmploymentΒ 

Tabasum Guledgudd is an experienced academic professional who previously served as an Assistant Professor at Sri Indu College of Engineering & Technology, Hyderabad, from January 2009 to May 2012. Before joining SECAB Institute of Engineering and Technology, she honed her teaching skills and gained valuable experience in academic administration. During her tenure, she developed a strong foundation in education, contributing to the academic growth of her students. Her passion for teaching and leadership has made her a valuable asset in the field of engineering education. πŸ“šπŸ‘©β€πŸ«πŸ«πŸŒŸ

Current EmploymentΒ 

Ms. Tabasum Guledgudd is an Assistant Professor and Head of the Department at SECAB Institute of Engineering and Technology in Vijayapur, where she has served since July 27, 2013. Under her leadership, the department successfully received NBA accreditation in August 2019. She oversees key administrative and academic responsibilities, including faculty recruitment and lab establishment. Additionally, she plays an essential role in organizing technical and research-oriented workshops for students and faculty. Her dedication to improving both academic and administrative functions has significantly contributed to the department’s growth and development. πŸŽ“πŸ“šπŸ«πŸ”§πŸ‘©β€πŸ«

Research Focus

Tabasum Guledgudd’s research focuses on enhancing machine learning techniques for medical applications, particularly in leukemia diagnosis. Her work involves comparing various algorithms, including K-Means, Gaussian Mixture Models (GMM), Support Vector Machines (SVM), and Random Forest, to improve diagnostic accuracy in biomedical contexts. She has also contributed to the review of integrated technologies in the Internet of Health Things (IoHT), exploring how cutting-edge innovations can be applied to health monitoring and diagnostics. Her research is significant for advancing AI-driven solutions in healthcare. πŸ’»πŸ©ΊπŸ“ŠπŸ’‘

Publication Top Notes

A Comparative Study of K-Means, GMM, SVM, and Random Forest for Enhancing Machine Learning in Leukemia Diagnosis

A comprehensive review: State of art integrated technologies in IoHT applications